Automated Author ProfileKallio, Eva R.
University of Jyväskylä0000-0003-2991-612x
Kallio, Eva R.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 6.7 (sum of 7 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
No description available
Authors
- Aminikhah, Mahdi ;
- Juha, Alto ;
- Jukka T., Forsman ;
- Hilppa, Gregow ;
- Heikki, Henttonen ;
- Otso, Huitu ;
- Mira H., Kajanus ;
- Erkki, Korpimäki ;
- Andreas, Lindén ;
- Jukka, Ollgren ;
- Hannu, Pietiäinen ;
- Jussi, Sane ;
- Janne, Sundell ;
- Leena, Ruha ;
- Yingying, Wang ;
- Sami M., Kivelä ;
- Eva R., Kallio
No description available
Authors
- Aminikhah, Mahdi ;
- Juha, Alto ;
- Jukka T., Forsman ;
- Hilppa, Gregow ;
- Heikki, Henttonen ;
- Otso, Huitu ;
- Mira H., Kajanus ;
- Erkki, Korpimäki ;
- Andreas, Lindén ;
- Jukka, Ollgren ;
- Hannu, Pietiäinen ;
- Jussi, Sane ;
- Janne, Sundell ;
- Leena, Ruha ;
- Yingying, Wang ;
- Sami M., Kivelä ;
- Eva R., Kallio
Additional file 1: Table S1. The population-level data of rodent abundance index and abundance index of infected rodents, including information about trapping sessions and the number of traps. Table S2. Population-level data on ticks including information about the number of collected nymphs and infected nymphs during 2019 and 2020. Table S3. The estimated effects of the treatments (removal, control and large islands) on the mean density of cervid dung in 2019. Table S4. The estimated effects of the treatments (removal, control and large islands) and the average density of cervid dung in 2019 on the density of nymphs on the island (DONt+1) in 2020. Table S5. Detailed information on primer and probes used for screening of B. afzelii. Table S6. List of all tested models. Table S7. The estimated effects of rodent removal treatment and session (May, June, July and August/September) and their interactions on the rodent abundance and the abundance of infected rodents on the experimental study. Table S8. The estimated effects of island size category (small control vs large) and session (May, June, July and August/September) and their interactions on the rodent abundance and the abundance of infected rodents in the observational study. Table S9. The estimated effects of the trapping sessions (May, June, July, August/Septe,ber), treatment (removal, control and large islands), and the rodent species (bank vole vs field vole) the larval tick infestation load in 2019.Table S10. The estimated effects of the study session (May, June, July, August/September) and rodent removal treatment on the density of nymphs (DON), the density of infected nymphs (DIN) and NIP in 2019 on experimental islands. Table S11. The estimated effects of rodent removal treatment on DONt+1, NIPt+1 and DINt+1 (May 2020) on the experimental islands. Table S12. The estimated effects of the rodent abundance index in different trapping sessions (May, June, July and August/September) on DONt+1 (May 2020) (a) on the experimental and (b) on the observational study islands. Table S13. The estimated effects of the rodent abundance index and the abundance index of infected rodents in different trapping sessions (May, June, July and August/September) on NIPt+1 (2020) on the experimental islands. Table S14. The estimated effects of the rodent abundance index and the abundance index of infected rodents in different trapping sessions (May, June, July and August/September) on the density of infected nymphs (DINt+1) in 2020 on the experimental islands. Table S15. The estimated effects of the rodent abundance index and the abundance index of infected rodents in different trapping sessions (May, June, July and August/September) on NIPt+1 (2020) on the observational islands. Table S16. The estimated effects of the rodent abundance index and the abundance index of infected rodents in different trapping sessions (May, June, July and August/September) on the density of infected nymphs (DINt+1) in 2020 on the observational islands.
Authors
- Kiran, Nosheen ;
- Brila, Ilze ;
- Mappes, Tapio ;
- Sipari, Saana ;
- Wang, Yingying ;
- Welsh, Erin ;
- Kallio, Eva R.
Additional file 1: Table S1. The population-level data of rodent abundance index and abundance index of infected rodents, including information about trapping sessions and the number of traps. Table S2. Population-level data on ticks including information about the number of collected nymphs and infected nymphs during 2019 and 2020. Table S3. The estimated effects of the treatments (removal, control and large islands) on the mean density of cervid dung in 2019. Table S4. The estimated effects of the treatments (removal, control and large islands) and the average density of cervid dung in 2019 on the density of nymphs on the island (DONt+1) in 2020. Table S5. Detailed information on primer and probes used for screening of B. afzelii. Table S6. List of all tested models. Table S7. The estimated effects of rodent removal treatment and session (May, June, July and August/September) and their interactions on the rodent abundance and the abundance of infected rodents on the experimental study. Table S8. The estimated effects of island size category (small control vs large) and session (May, June, July and August/September) and their interactions on the rodent abundance and the abundance of infected rodents in the observational study. Table S9. The estimated effects of the trapping sessions (May, June, July, August/Septe,ber), treatment (removal, control and large islands), and the rodent species (bank vole vs field vole) the larval tick infestation load in 2019.Table S10. The estimated effects of the study session (May, June, July, August/September) and rodent removal treatment on the density of nymphs (DON), the density of infected nymphs (DIN) and NIP in 2019 on experimental islands. Table S11. The estimated effects of rodent removal treatment on DONt+1, NIPt+1 and DINt+1 (May 2020) on the experimental islands. Table S12. The estimated effects of the rodent abundance index in different trapping sessions (May, June, July and August/September) on DONt+1 (May 2020) (a) on the experimental and (b) on the observational study islands. Table S13. The estimated effects of the rodent abundance index and the abundance index of infected rodents in different trapping sessions (May, June, July and August/September) on NIPt+1 (2020) on the experimental islands. Table S14. The estimated effects of the rodent abundance index and the abundance index of infected rodents in different trapping sessions (May, June, July and August/September) on the density of infected nymphs (DINt+1) in 2020 on the experimental islands. Table S15. The estimated effects of the rodent abundance index and the abundance index of infected rodents in different trapping sessions (May, June, July and August/September) on NIPt+1 (2020) on the observational islands. Table S16. The estimated effects of the rodent abundance index and the abundance index of infected rodents in different trapping sessions (May, June, July and August/September) on the density of infected nymphs (DINt+1) in 2020 on the observational islands.
Authors
- Kiran, Nosheen ;
- Brila, Ilze ;
- Mappes, Tapio ;
- Sipari, Saana ;
- Wang, Yingying ;
- Welsh, Erin ;
- Kallio, Eva R.
No description available
Authors
- Aminikhah, Mahdi ;
- Juha, Alto ;
- Jukka T., Forsman ;
- Hilppa, Gregow ;
- Heikki, Henttonen ;
- Otso, Huitu ;
- Mira H., Kajanus ;
- Erkki, Korpimäki ;
- Andreas, Lindén ;
- Jukka, Ollgren ;
- Hannu, Pietiäinen ;
- Jussi, Sane ;
- Janne, Sundell ;
- Leena, Ruha ;
- Yingying, Wang ;
- Sami M., Kivelä ;
- Eva R., Kallio
Files description:RT_workflow.qmd (quarto file that shows the R code)RT_workflow.html (online html file created from the quarto file)Input files needed for the R workflow (qza files extracted from QIIME2 and text files)For general queries, unexpected errors and/or inconsistencies, please contact [email protected].
Authors
- Scholier, Tiffany ;
- Lavrinienko, Anton ;
- Kallio, Eva R. ;
- Watts, Phillip C. ;
- Mappes, Tapio
Files description:RT_workflow.qmd (quarto file that shows the R code)RT_workflow.html (online html file created from the quarto file)Input files needed for the R workflow (qza files extracted from QIIME2 and text files)For general queries, unexpected errors and/or inconsistencies, please contact [email protected].
Authors
- Scholier, Tiffany ;
- Lavrinienko, Anton ;
- Kallio, Eva R. ;
- Watts, Phillip C. ;
- Mappes, Tapio